Predictive modeling for non-performing assets in the indian banking sector

Authors

  • Suresh B Pathare School of Mathematics, Applied Statistics & Analytics, School of Commerce SVKM’s NMIMS (Deemed to be University), Navi Mumbai, Maharashtra
  • Mohneet Sandhu School of Mathematics, Applied Statistics & Analytics SVKM’s NMIMS (Deemed to be University), Navi Mumbai, Maharashtra

DOI:

https://doi.org/10.3329/jsr.v58i2.80616

Keywords:

Nonperforming assets, Indian banking sector, Credit underwriting, Monitoring systems, Risk management, financial impact, Profitability, Provisioning requirements.

Abstract

This paper explores the financial and operational factors that contribute to India’s Nonperforming Assets (NPA) problem and discusses practical solutions for mitigating the risk of future NPAs. Descriptive statistics, regression analysis, and time series analysis are used to identify the main drivers of NPAs of Indian banks, revealing that high levels of NPAs have resulted in lower profitability, increased provisioning requirements, and higher borrowing costs. The findings and recommendations of this study provide valuable insights for policymakers, regulators, and banking practitioners seeking to reduce the risk of NPAs in India.

Journal of Statistical Research 2024, Vol. 58, No. 2, pp. 335-351

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Published

2025-03-25

How to Cite

Pathare, S. B., & Sandhu, M. (2025). Predictive modeling for non-performing assets in the indian banking sector. Journal of Statistical Research , 58(2), 335–351. https://doi.org/10.3329/jsr.v58i2.80616

Issue

Vol. 58 No. 2 (2024)

Section

Articles

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Copyright (c) 2024 Journal of Statistical Research

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